2013 IEEE Symposium Series on Computational Intelligence

QCCI 2013

Although quantum computing is still in its nascent days,
there are experiments that successfully perform quantum computation
on a small number of qubits. Recently, researchers at the NIST
demonstrated continuous quantum operations using a trapped-ion processor.
Other researchers have discovered a way to make quantum devices
using technology common in our current chip-making industry.
Historically, classical computer concepts and underlying technologies
have been invented by mathematicians and physicists rather than engineers.
It was engineers, however, who took basic concepts and ideas and
created the practical powerful and inexpensive computers of today.
We believe that the same will happen in case of quantum computing.

As quantum information and computation research continues to develop, we will see increasing interest in adapting the philosophy of quantum computing, information theory and ideology into other, more traditional aspects of computational research. Although the hardware technology to realize quantum computing still yet to be materialized, research about the theoretical aspects of quantum computing and its ideology has enjoyed some success with artificial and computational intelligence.

This symposium focus on combining various aspects of quantum computing, information theory, and other aspects with existing fields in computational intelligence.

Topics

Some typical research areas that will be discussed in this special session include (but are not limited to) the following:

Evolutionary Techniques and Quantum Computing. Including: (a) use of evolutionary paradigms to create quantum circuits, quantum algorithms, quantum architectures and quantum games, (b) creation of new quantum algorithms and architectures inspired by the concepts of evolution and other biological ideas, (c) use of evolutionary algorithms to solve any practical problems in designing quantum devices.

Quantum implementation of Computational Intelligence: many machine learning and problem-solving models known from Computational Intelligence such as Neural Nets, Bayesian networks, Logic Networks, Fuzzy Logic, state machines, evolvable hardware, etc., can be extended to those based on quantum circuits and automata.